Difference between revisions of "Teppei Syokudo - Improving Store Performance: Project Management"
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<p> Undergraduate Conference for Data Analytics Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted</p> | <p> Undergraduate Conference for Data Analytics Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted</p> | ||
− | <p> Undergraduate Conference for Data Analytics Paper 2 - Identifying Labour Productivity in F&B store using Regression Models Submitted/p> | + | <p> Undergraduate Conference for Data Analytics Paper 2 - Identifying Labour Productivity in F&B store using Regression Models Submitted</p> |
<p> Final Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted</p> | <p> Final Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted</p> | ||
<p> Final Paper 2 - Evaluating and Establishing KPIs and Staff Performance in F&B store Submitted</p> | <p> Final Paper 2 - Evaluating and Establishing KPIs and Staff Performance in F&B store Submitted</p> |
Revision as of 02:09, 16 April 2016
Current Progress
Undergraduate Conference for Data Analytics Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted
Undergraduate Conference for Data Analytics Paper 2 - Identifying Labour Productivity in F&B store using Regression Models Submitted
Final Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted
Final Paper 2 - Evaluating and Establishing KPIs and Staff Performance in F&B store Submitted
Interim Report Submitted
Interim Wiki Updated
Timeline
Limitations and Assumptions
The greatest limitation and assumption that the team is currently working on is the integration of the data from the POS system and the current data obtained. Another limitation that the team faces is the availability and format of which the data is stored. Ideally with data of sales made by each transaction, the person making the sales should be recorded. If that information can be aggregated then we’d be able to more efficiently analyse staff productivity.